{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-20T09:54:42.934683Z",
     "start_time": "2020-12-20T09:54:42.495277Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 子图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 使用 plt.subplots 绘制均匀状态下的子图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列\n",
    "\n",
    "figsize 参数可以指定整个画布的大小\n",
    "\n",
    "sharex 和 sharey 分别表示是否共享横轴和纵轴刻度\n",
    "\n",
    "tight_layout 函数可以调整子图的相对大小使字符不会重叠"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T02:06:07.242097Z",
     "start_time": "2020-12-19T02:06:06.524914Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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jw0M7jZ+IyIyLydrr+g5eayZvTyBFLWtmg6nMv/tWTR0WkPTbOwGMp8Nm4PR0uErSLOA2kiYRu0XE77tb5HKY6kMFfEm7HBpr/mdITETsME9jXDQ7g/cdvJZlKlcCfBVhcPiYYEUp++++Va8OvwMeBTYBRwFfBu4G/gT4F+ARkkR4Uzrfg10raclMJUlxbXG5LDtgEdcsfxm/OetVbG9IemvaiQvfwTu4ulm74j7Hy8/HBCtS2X/3rdr4LiBJarcD/xe4j6TW9w3AGPCPwKXpvMPA7K6UsoRa3aQ0GT+CdvC0WxszlZvXfAfvYOp27Yr7HC+f+v3A/LnDjG0cp/GU2ceEauhGTX/Zf/et2vhuSNv5bgNmAddFxLuBZwCfBj4LfCmZNTZHxIaul3jANKvJyWrb2U6SsnLdaGZiBOUJyrLJUxszWVy0Wo/76x1MeWpXOqkZbnYyHdByHb6K0H9OW3kz77vkxsf3Aw9nJL01PiYMnjy/8W7V9Jf9d5+nH9+TSZo+kCbC50i6HFgWEdsnXbJiamdgo2ObEDy+U8qqyfnIqlsZ2zQOwJzhyVue1IK8mbIEZdnkqaGfrPuZw85a3XI9voN38LRbu9JpzXDWlYCaVuvwVYT+snLdKBded3fTRLeRjwmDJe9vvFtXf8v+u2878Y2IX2SMuwf4XKElGnCNgdvq8tOWbU+cMzy8cTx3kNeUKSjLJu9lI9+8Vi3tNnvq9CBXfzKV9Tn1tcvNLpn6pqn+sOKK9W0nvT4mDJ5mv/EPfP0m3nfJjTv9/rp1TCj77z7Xk9skzQC+CHwqIm5pmDYbGIuISp9iTpac1tSCsqindgFTuqTtu4G7ayrtubuxHusv7dauTOUgVzuZ2nv5ZZmJU61mqVlNk/cH/aHdhGZIcjOnAdRs+9Z6+mn8Xc6fO8zDG8d3mr+IY0L9776WI2Ql34OoVa8OpA+uqDkXOBh4WNIcSd+vm7bzf7+C8tx938lTu7Ismj8ypaTXdwN3V6ftubu1HusftQPKpvEJhiSgedvsItrdNZt3SCr1Xdxl0e62nohgxRXrvR8fMO1s39rvcuW6UR7dvG2n6cNDKvSYUMYcoWXiC/y7pHMlfQZ4EfDSiBgl6dv30NpMaTvf3MmvpPMkXSvptLzL9qNWgVufqOQ9kHUj8Sl7tyX9IOums9cflDxwIs9NSr55rVzqDyiQJCu133Oz9rZT/f03W0dj39E1bkbTX5o98CZLGRKUqml3+9ae9jq+feff7bxZMws9JpQxR2gn8f0SSY8Ofw1sAQ4CiIhxYOtUPlzSscBQRBwKPFvSc6ayvn6QFbhK/zYmKnkPZN1IfNxudHrU99V78pGLuXTtaEdn0PXruWb5y5z0DrC8B5Qifv/N1rGo5Hdxl0XW9lswd7jp/IOeoFRN4/atXQVqtHD+SNNj9IZNxV58L2OO0LKNb0RcDFws6UTgJOBSSasi4m0FfP5S4Ovp6yuBlwC/qk2UdDxwPMBee+1VwMd1X55G4Z00IC+6vd0gthsdxLio536Yu2PQ4qKTA0oRv/9m6yjrXdyDFhetNG6/vZdfNun8rRKUqt7j0a9x0di2ttnvstnNqkUfuwcxR2il1SOLR4AtEbE9Ih4BTpf0ZeDodJZ2bzBtZh5Qq+b6PXBg/cSIOJekXTFLliyZ6mdNmzwHp17fODKI3ZYMalzUlPEMuh8MWlz00wGlzHdxD1pc5NUsjuqnN1P2R9NOZhDiotXvcjqO3YOYI7TSqsb3MSC0c3W7JH0hfTHRMH8ejwK1X+UutNf0wgpU5gNev+qnhMd6p98OKL0+CbfOTNZPc6t48tWn/tfsdzldx+4y5gitEt8XA5vZ8aa13YEHSZquXpPOQ/r+pzk/fy1J84brgP0BN0bqAR/wple/JTzWG2U8oNj0a+yneUhiIoJFbcSTrz4Ntuk6dpctR5g08Y2I6+rfSzoYuAh4V0R8W9L2iLi1bnrez18J/FjSQuAo4JC8KzAbNFkJz+H77F6qfhKtPWU7oFhvdBpHvvpkVdTy5jZJbwLGSNrifgdYERHfLuLDI+IRSUuBI4BPRsSGItZr1u8mu4GhSu3srD9V9Yanflf0dvHVJ6uidp7cdgDwHpIuzb4L/C8ASbOA2VMtQEQ8zBM9O5hVTift7JyYWLf4RKw/dWO7LDtgEWv+3++5+Pp7mIhgSOL1B/kqRK9Nx/69yseQljeTRcQpwG4k3X48E7hD0pHAEHBzbb70CW/NOxQ0s0x529mV8Uk61j/K2GF9GXRju6xcN8qla0cff4DJRASXrh31vqSHJtu/r1w3ymFnrc714KO8n1EFbfWiEBGbI+JLJDegfQz4LLA9Il5UN9tMnPhOWVGBbYMj7xP8nJhYN/mGp/7Uje3ifUn/abZNPvpvtxaWrFZ9u+fqPiwSXwL2i4gtDdO2AG8tsnBVU/WzsKrK+wQ/JybWTXlPxGx6FLVd6itXmvX/631J7zT73z+8cbywZLXqx5CO+s1tTHol7SXpIuCi9GY460DVz8KqKu+jaJ2YDLZ+v6qT90TMpkcR26WxcqUZ70t6J+//vpNkterHkHZubsskaXeSRw6/EXgdcCewLCL+rZiiVU/Vz8KqLE93RL4Te3ANwo1j7l+4PxWxXbIqVxp5X9Jbzfbvs2fOYGzT+E7zd5KsVv0Y0uqRxZ8D/gjYSvKEtfnpsAh4OskDJ1YCSyPi2i6WsxLcp6K1w4nJ4OqHJ2W1cze3+xfuT1PdLpNVogi8L+kDzfbvUNwjiqt+DGlV4zsO/AHYRtKX7xiwIB03BjwXOBrYIuk3EXF/twpaBVU/C7P2OTEZTL2+qjMINc7WPc0qVxbNH+Ga5S/rQYksy2T796KS1SofQ1o9ue39zaal3Zd9nOTxxYcDH5L0CeB/RsS2QktZEVU/CzMru15f1emHGmfrHVeuDLYqJ6tF6qiNr6RdgW8CTwbeExFnS3opcB6wN/CO4opYLQ5ss/LqdeLR6xpn6y1XrphNkvhKGgF+CzwKbAQmSJo8jANPA+YCZwPzJc2NiB9LOhTYo+ulNjMbQL1OPHpd42y958oVq7rJanwngP9GkuhuTf8OkTym+GkkT3HbHzgR2EXSpcAnIuKWrpbYzGyA9TLx6HWNs5lZrzVNfCNiK/Cd2ntJHwUuioj1dePeA7wZ+BBwDLBO0mkR8YnuFdnMzDrR6xpnM7Nea9Wd2ayI2CppIbAPsFbSV4DTIuL3wLtJkuM5wCrggyS1w2Zm1od8qdvMqqzpk9skzQXukXQ+sEdEHAcsBv4KuEnS24FfkjR3+Abwxoj4ofvzNTMzM7N+NNkjiydIeme4H/iapB8CLwIC+C/Am4A/B14TETcD8yS9pMvlNTMzMzPrSNPENyK2RMTlEbE8Ip4LnAa8H9gCDAOvAr4K3JAu8l3gxV0ur5mZmZlZR9ruxzftrmwpMBQRW9LR76qb5b0RMflDwM3MzMzMeiTXAyzSJ7JlPpXNSa+ZmZmZ9bPJ2viamZmZmZWGE18zMzMzqwQnvmZmZmZWCU58zczMzKwSnPiamZmZWSU48TUzMzOzSnDia2ZmZmaV4MTXzMzMzCrBia+ZmZmZVYITXzMzMzOrBCe+ZmZmZlYJTnzNzMzMrBJ6kvhKminpbklXp8O+vSiHmZmZmVXHzB597n7AxRFxSo8+38zMzMwqpldNHQ4BXi3pBknnSepVAm5mZmZmFTEtCaekc4DFdaOuAl4eEb+V9BXgaGBVxnLHA8enb7dIuqXrhe29pwAP9boQ02Bx61myOS5KzXGRTxXiouOYAMdFiTku8qlCTEAbcaGImI6C7Pih0uyI2JK+PhEYjoizWyyzJiKWTEsBe8jfszfr6Xf+nr1ZT7+rwvcs8jtW4f8F1fiejot8qvAdob3v2aumDhdI2l/SELAMuKlH5TAzMzOziuhV29rTgYsAAasi4vs9KoeZmZmZVURPEt+IuIWkZ4c8zu1GWfqQv2dv1tPv/D17s55+V4XvWeR3rML/C6rxPR0X+VThO0Ib37MnbXzNzMzMzKabn9xmZmZmZpXgxNfMzMzMKsGJr5mZmZlVghNfMzMzM6sEJ75mZmZmVglOfM3MzMysEpz4mpmZmVklOPE1MzMzs0pw4jsNJP2lpBPS1zMlzaibNkPSrN6VznrFcWFZHBeWxXFhjRwTnXHiWzBJb5X05br3zwD+HrgyHXU8sEbSGklrgLXUPWJP0gmS7k+n752OO1DSTyVdJykk/SQdrpW0v6Rd0/lul7T/dH1Xa99U46LJOhwXA66A/cVySRskjUn6QDrOcTHgCoiLgyV9W9IVko5KxzkuBlgRx5B0uXdIOj99Xc2YiAgPBQ3Aq4Ex4Pz0/S7AOuD1bS6/LzAKLAQOBS5rmP4C4K6GcfsB96WvbwT27vX/wUOxcZG1DsfF4A8F7C8OBW4Cng08D3gE2NNxMdhDAXGxK3AHcDiwFPhPYIHjYnCHIo4h6XK7Aw81HkeqFhOu8S3WO4CP1b1fBFwA/ELSz2pnT5NYBnwlIu6LiGuBp0iaVzf9lUBI+kw6vBT4A7Cxbp6Y8rewok01LrLWUc9xMZimGhcbgbdExK8j4jbgLpKT5hrHxWCaalw8HTgtIq6KiKuBe4Bn1E13XAyeIo4hAJ8GvpcxvlIxMbPXBSiZNwB/UXsTEesl3UFyKeJCYG9Jl5MEVACzgW3AMPA1YAFwdd367gOeCdwmaTbwTuBk4E7gDJIz+3u6+5WsAFOKi4hY3riOGsfFQCsiLgCQtBDYE7glfe+4GFxFxMXtkoZIKlOGgdvAcTHAphwTko4gOQH6aP26qhgTTnwLFBEhqXH03wMvB94YEWPU1chI+ipJUH4nff9FksuVNY8B89PX/0ASlD+PiF9L2pPk8oO3YZ+balxMsg5wXAysIuKizseBcyLisfS942JAFRgX7yWJiw9GxEQ6znExgArILUaATwHHktQW16tcTJT2i/UDSa8jCbQ721zkYZ5IdAFGgO1pIL4FeDNwjaSzgVkRca+kZxVXYpsOHcRFs/U4Lkqk07hIb156CUk7PcdFyXQaFxHxKUlfB66XdAWwBcdFKXQQEx8GLoiIX0l6PPGt6r7CiW93/QC4Hvh+m/OvAV4KXKjk9O5AYDQi7pG0OCLG07Y31wGfSJeZi7fjoMkbF5kcF6WTOy7SA9cXgWNqtb2Oi9LJFReS/gSYGxG/SBOYnwGLI+Iyx0Vp5N1XvIbknqH3A7OAEUlPjohjqxgTpfxS/SIiHgUebXKJOst3gU9JWg08H/hdRNyTrms8nedgkrs7P5++f5DkUoUNiA7iYrJ1OS5KIm9cpG3zVgErIuKGhnU5Lkqig/3FQuAcSYeSXDU8GPgf6bocFyWQNyYi4s9qryUtBd4eEW9Pp1UuJpz4To8ZwOMRqqST6dkkDcgfv1MyIh6R9AZgBcllqbfWLfMk4O+AtwFHRMSmdJkHJX01bcMzr3591vfaiovJOC5Kqd24eCVJ84anS6rd6Pa3EXGp46KU2j2O/EjSV4BfktwnclJE3Jcu47goFx9DOqCI0nyXviXpTuCwiHggfS/gpyRB+8aIuLuNdfwQmADeFhH3NkybC9wPPADsVwtc62+OC8viuLAsjgtr5JjojBPfASFpN2AsIrY3mf6UiHhomotlPea4sCyOC8viuLBGVYwJJ75mZmZmVgk9e3KbpJmS7pZ0dTrs26uymJmZmVn59fLmtv2AiyPilB6WwczMzMwqomc1vsAhwKsl3SDpPEnuYcLMzMzMuqZnbXwlHQzcGxG/Tbte+WZErGqY53jgeIB58+YdtM8++/SgpNYNa9eufSgidu9kWcdFeTkurNFUYgIcF2XluLAs7cRFLxPf2RGxJX19IjAcEWc3m3/JkiWxZs2aaSufdZektRGxZKrrcVyUi+PCGhUVE+C4KBPHhWVpJy562dThAkn7SxoClgE39bAsZmZmZlZyvWxXezpwEclTR1ZFRNvPpzczMzMzy6tniW9E3ELSs4OZmZmZWdf1sqmDmZmZmdm0ceJrZmZmZpXgxNfMzMzMKsGJr5mZmZlVghNfMzMzM6sEJ75mZmZmVglOfM3MzMysEpz4mpmZmVklOPE1MzMzs0pw4mtmZmZmleDE18zMzMwqwYmvmZmZmVWCE18zMzMzq4SZvS6Ame1o5bpRVlyxnvvGNrFw/ggnH7mYZQcs6nWxzMzMBp4TX7M+snLdKKd+62Y2jU8AMDq2iVO/dTOAk18zM7MpytXUQdKwpAMyxr+2uCKZVdeKK9Y/nvTWbBqfYMUV63tUIusXK9eNcthZq9l7+WUcdtZqVq4b7XWRzMwGzqSJb5ro/qOkuemoBcC1ddP3kXQ9cKmkZ3WvmGbVcN/YplzjrRpqVwJGxzYRPHElwMmvmVk+rWp8twMfBobS91uBzQCSXgOsA+4H9o2Iu7pURrPKWDh/JNd4qwZfCTAzK8akiW9ETKR//1AbRZIMA6wF3hkRr4uI27tXxGryZc1qOvnIxYwMD+0wbmR4iJOPXNyjElk/8JUAM7NitHNz20TD+7mSPlt7I+mF6cuNwL9GxH8UVbiq8g1O1VXbvu7VweotnD/CaEaS6ysBZmb5dNKrQwBbMsYfBjwHeP2USmSTXtZ0AlR+yw5Y5O1sOzj5yMU7nAyDrwSYmXWik8R3U0ScLGk+8NSIuANA0jHAJ4osXFX5sqaZ1fOVADOzYkya+EoaBmZKmhMRmwHxRLvg1wFflPQ14CzgKuAFXSxrZfiyppk18pUAs/LzA4y6r1WNr0hqcWdIGgJGgFrXZt8AbgVOILnR7YMR8fluFbRKfFnTarwTLDdvX5tOjrf+5vt7pkerXh22RsSpEbERuBw4GvhTSccB64E9IuKvgUOA1V0vbUUsO2ARZx67L4vmjyBg0fwRzjx2Xwd+xbjv1nLz9rXp5Hjrf+62cHq0auqwgKTf3glgPB02A6enw1WSZgG3kTSJ2C0ift/dIleDL2uab3Ist+navq7lM/D+ZBBM5/09Vd4vtGrq8DuSXhxqjqp7/S/poHSe2t8dOyEtmSoHi3Wuk7jxTY7lNh3b15dOrcb7k/43Xff3VH2/0OrJbQtI2vXOJmnq8EXgn4EHgV8BbwaGgVkkbX9361pJ+4AvFVknOo0bP8Wt3KZj+/rSaTl18oCj+XOHM8d7f9I/pusBRlXfL0xa4xsRG2qv0yYN10XElyWdBPwV8FngVcA70l4fNnexrD3XzUtFk9UIdjrN+kOnceObHMttqtu3nd9+J7V83qf0t05q61auG+XRzdt2Gj88JO9P+ki3ui1s/E1n1SpDdWr/8/TjezJJ0wciYhtwjqTLgWURsX3SJUuiW5eKsnZkJ11yIx9ZdSuv3v/pXLp2NHMnB1T6csWg6DRu3HdruWQllGceu29H27fd5CfvpdOqXwIdBJ2cSK+4Yj3j22On8fNmzfR27TNF39+T9ZuutUttVJXa/7YT34j4Rca4e4DPFVqiPtat9jdZOzKAsU3jXHjd3TsFaP0lCd+s0P+mEjdF7QRdi9dbzRLKM4/dl2uWv2yH+Q47a3XL7dRu8pO3Vtk3QPW/Tk6km03bsGm8kDJZ/8r6TdfflFVTpauJrdr47kDSDElfkvT8jGmzJZW6nrxb7W8m22FlnZXVlvHNCoNhsrjppK1eXm6b3nvttKnLs53a/e3n7RrR+5T+10nbcN8vUF3NfrsBle0ytWXimz64ouZc4GDgYUlzJH2/blrpTx271b9uJzufhfNHvDMbEM3iBpiWhLTqNzL0g3YSyjzbKc9vf9kBi7hm+cv4zVmv4prlL5t0f+V9Sv/rpAJmum6asv7T7Le7aP7I4/uFk49czIor1ne1AqaftNPU4d8l/QbYCLwIeGlEjKWPMz60NlNEbJeUO/mVdB7wPOCyiDgj7/LTrRv962Zdjqw32SUJ3/w0GLLi5rCzVk/LZWXX4vVeO81d8mynbt346Bsq+18nbf9bLeOmUOXV6jddxXb97SS+XwKOBN4C3A4cBPwgIsYlbZ3Kh0s6FhiKiEPTJhTPiYhfTWWdg6gWXB/9t1t5eOOO5w4jw0O8/qBFXHX7g013St5hDabpSkinq29Ia66dhDLPdurWjY++oXIwdFIBU1umluS+75IbWXHFeg7fZ/emN1B7uw++Vr/pKrbrb5n4RsTFwMWSTgROAi6VtCoi3lbA5y8Fvp6+vhJ4CUn/wABIOh44HmCvvfYq4ON6p9UZdeNOaXRsE0MSm8YnuOr2B5sefKr4hLeyxEUnCWknNTNVqcXr57hoJ6HMu53qf/v1ycxUk9Wy7VP6OS66KWtfATv3BDTZDdRlioNGZYyLZseHyX7TVbwi2OqRxSPAlojYHhGPAKdL+jJwdDpLs3uv2jUPqDUm+T1wYP3EiDiXpF0xS5Ysmepn9UyeSwm1943zn/zNm/jIqlvZsGm88rUwZYmLvIlOp5ekqlKL1+9x0Sqh7HQ75Y2Lql3W7ve46FSr/t2zYmLO8IzMO/yzlDnxgfLFRafHhypeEWxV4/sYEJIax0vSF9IXEw3z5/EoyZPhAHYhZy8TgyLvpYSs+ccngrG06xlfiiqHvInOVC5Jla0Wr6w62U554qKK7fnKqNV2bBYTze4jyVLmxKeMmm3zky65kZMuuZFFTY4vVbkiWK9V4vtikqex1Tc83Z3kkcUCrknnIX3/05yfv5akecN1wP5AKW8zb3bmPDq2KbPPznbOtKtwKarfdKOmLE+iU8VLUlXWbrzliYsqtucro1bbMe8+ocp9upZFq23e7CS3vgKmvollrTeZMu4XWj2y+Lr695IOBi4C3hUR35a0PSJurZue9/NXAj+WtBA4Cjgk7woGQbNLCYLHx9cH5WSPFKznhGf6dPqY0E4uWzdbpoqXpKoqT7zliQufPJVDq+3YLCbmjwyzZdv2nWr3Wt1Abf2vnbyh2UlusyaWZb0a1E4/vm+S9EpJ+wLfAT4VEd8u4sPTdsNLSWp8D4+IDUWst99k9aGY9cjAWlBmzZ/FCc/0ydsXbicPjWi1jPvirI488ZYnLtxPbzm02o7NYuIjr/2zzD7Fz1i2b9t9PVt/ajdvaHbSVKX+3tvpzuwA4D3ALOC7wP8CkDQLmD3VAkTEwzzRs0MpZbXlbHZmdt/Ypp3mnz93mEc3b9vhWetOeKZX3pqyTi4pt1qmKjepWb54yxMXVWzPV0attmOrmJhsn1G1mx8HzWQ9NwB84Os3MRHN79VrdtJUpatB7XRndoqkD5P043sScIekE4AfATfX5kuf8DbcpXIOvMa2nIedtXrSy5ON83tn1Ft5mxm02olkbc92djy+Sa0a8sZbu3Hhk6dyaGc7drKv8M2P/a3V9slqslBvspPcKjWla6fGl4jYDHwp7crsHcBngf0i4kUN63Li26ap9Nlp0y/v9ppsJ9Js57XryPDjPXc0LmPV0s2aWe9L+lurSo7G6Z8+7gWFbU/f/Njf2tk+WTerTUQ07dWhpkpXg9pKfGsiIkgS4AsjYkvDtC2S3lpo6UrMNS+DJe/2mmwn0mznNWd4BiPDQ5XY8djkvH+oplY1et2uka3S5e5B1O726fTJflCNfU6uxLemMemVtBdwFnCcJEXE14ooXNm55mWw5Nlek+1E3nfJjZnLjG0c59PHvaASOx5rzfuH6mlVo9ftGtkqXe4eRK22z1SbRFZln9NR4gsgaXeSHhneCLwOuBNYFhH/VkzRzAZbs53IZDuvqux4zGxnrWr0ul0jW6XL3YNosu3j9tnta/XI4s8BfwRsJXnC2vx0WAQ8neSBEyuBpRFxbRfLaVYaPriYWZZWNXrdrpGt0uXuQTTZ9jnsrNVun92mVjW+48AfgG3AWDosSMeNAc8Fjga2SPpNRNzfrYKalYUPLmaWpdVJ8XScNPuqU39rtn3cPrt9rZ7c9v5m09Luyz5O8vjiw4EPSfoE8D8jYluhpTQrGR9czKxRu/3v+qTZGrl9dvs6auMraVfgm8CTgfdExNmSXgqcB+xN0uWZmZmZ5dDqpNgnzZbFTeja1zTxlTQC/BZ4FNgITJA0eRgHngbMBc4G5kuaGxE/lnQosEfXS21mZmZmgK8G5DFZje8E8N9IEt2t6d8hkscUPw14JrA/cCKwi6RLgU9ExC1dLbGZmZmZ7cBXA9ozo9mEiNgaEd+JiCsi4irgCOD+iLgyIi6IiDNIHlu8EDgD2AdYJ+mUaSm5mZmZmVkOTRNfAEmz0r8LSRLbtZK+IGm3dJZ3A3sCc4BVwMtJkmEzMzMzs77SNPGVNBe4R9L5wB4RcRywGPgr4CZJbwd+SdLc4RvAGyPih+7P18zMzMz60WQ1vhMkvTPcD3xN0g+BFwEB/BfgTcCfA6+JiJuBeZJe0uXympmZmZl1ZLI2vlsi4vKIWB4RzwVOA94PbAGGgVcBXwVuSBf5LvDiLpfXzMzMzKwjbffjm3ZXthQYiogt6eh31c3y3oiY2GlBMzMzM7M+kOsBFukT2TKfyuak18zMzMz62aS9OpiZmZmZlYUTXzMzMzOrBCe+ZmZmZlYJTnzNzMzMrBKc+JqZmZlZJTjxNTMzM7NKcOJrZmZmZpXgxNfMzMzMKsGJr5mZmZlVghNfMzMzM6sEJ75mZmZmVglOfM3MzMysEnqS+EqaKeluSVenw769KIeZmZmZVcfMHn3ufsDFEXFKjz7fzMzMzCqmV00dDgFeLekGSedJ6lUCbmZmZmYVMS0Jp6RzgMV1o64CXh4Rv5X0FeBoYFXGcscDx6dvt0i6peuF7b2nAA/1uhDTYHHrWbI5LkrNcZFPFeKi45gAx0WJOS7yqUJMQBtxoYiYjoLs+KHS7IjYkr4+ERiOiLNbLLMmIpZMSwF7yN+zN+vpd/6evVlPv6vC9yzyO1bh/wXV+J6Oi3yq8B2hve/Zq6YOF0jaX9IQsAy4qUflMDMzM7OK6FXb2tOBiwABqyLi+z0qh5mZmZlVRE8S34i4haRnhzzO7UZZ+pC/Z2/W0+/8PXuznn5Xhe9Z5Heswv8LqvE9HRf5VOE7QhvfsydtfM3MzMzMppuf3GZmZmZmlTAQia+f9FYeRW5Lx0U5FL0dHRfl4LiwLI4Ly5JnOw7KgyMq8aQ3SecBzwMui4gzel2eLilyWzouyqHo7ei4KAfHRU4ViAlwXOTmuNjRQNT4UoEnvUk6FhiKiEOBZ0t6Tq/L1CVFbkvHRTkUvR0dF+XguMihIjEBjotcHBc768vEV9I5ddXVVwO7kzzp7YXAMMmT3spmKfD19PWVwEt6V5Su+hkdbkvHRWnjouOYAMcFjotMFYyLpZQ/JsBxkddSHBc76Mszm4j4m/r3qnvSG7AGKOMZyzxgNH39e+DAHpalm37R6bZ0XJQ2LjqOCXBc4LjIVMG4qEJMgOMiL8dFg76s8c1QhSe9PQqMpK93YXC2TV5FbkvHRTkUvR0dF+XguMinCjEBjou8HBcNBuUfcDpwAXAjcG1Jn/S2licuQewP3NW7onRVkdvScVEORW9Hx0U5OC7yqUJMgOMiL8dFAz/Aok9IejLwY+AHwFHAIRGxobelsl5zXFgWx4U1ckxYFsfFzpz49hFJC4AjgB9FxP29Lo/1B8eFZXFcWCPHhGVxXOzIia+ZmZmZVcKgtPE1MzMzM5sSJ75dJunpkmb3uhzWXxwXlsVxYY0cE5bFcdE5J75TJOlUSf/cMO6Tkj6Yvv0m0PLZ35IOlRSS5rUx7/x03j9K38+WNCtjvplZ4637HBeWxXFhjRwTlsVx0T1OfKduM7AVQNIrJN0JvAP4gKRbgBcAX5P0S0n/vX7BNIjfUrcegC3ptLdI+r6k4YzP3NSwzEeBLZK21Q3bgXHg74r5mpaT48KyOC6skWPCsjguuqQvn9w2CNKgeRowFxiRtCdwFUk/eR8CHo6Izyh5JOL7gNsalh8B3gO8IR01DhAR29L3RwJ3RcR4xsdPNPw9Azg9IjbWrX8G8KS6eWwaOC4si+PCGjkmLIvjovuc+HbumcCv6t6/Fng2yZlSY1cZQXLmNlfStoiYAN4MzAbubVyxkn733gCc1zB+f2BFui6AS9PLDUc3BnFEbAcq3VdfjzguLIvjwho5JiyL46LL3J1Zh9KznjnAd4CbgeXAvwAHA9tJno/9VOA3tUVIHht4FElQ3wTcDbwQeBWwEbg5IiTpH0keuTcbuA44PiImJD2D5GztRcA7SS57DAOXkVyiaNyYAmaRnCFuxbrOcWFZHBfWyDFhWRwX0yAiPHQ4kATnJuAzGdOWAlc3We4vgf9HEnwnA/cDh5ME114kZ1OvAHYDbgHOb1j+f6fz7gn8CcmljEeAMZKzwi3p6w0kZ3AH9fp/VaXBceHBceHBMeHBcdGfQ88LMMgDyZNQguRxgP8d2CcN1ltIzsYeS1/fBjyQLjOH5Kzs6PT9DOAY4Pnput4FXFj3GXsC+9W9HwYeSOf9FfAm0pr7dPo/AZ/v9f+myoPjwoPjwoNjwoPjoj+HnhdgkAdgJXAt8F3gQeCVwI3ptKWkZ2XAfODuuuVGSBquz+aJ5ibPByJ9XRs3Cxhp+My/Adanwfk3wCiwC/B2YEEtOIFFwGt7/T+q4uC48OC48OCY8OC46M/BbXw7JOmVwIUkwfA04GLgIZI2ObeR3PW4kCSQhoAFEfGsuuVvAPYjuXQQJGdnT2LHRuOzgWsj4mXpMnsCa4D3pp/3ZJLLGL8l+ZE8H/hrkjO/64F/BQ6MiB3u+rTucVxYFseFNXJMWBbHRfe5H9/ObSMJzE0AEXE9SZDdERFLSM6Y1qavD6fhfx0RL4yIORGxa0TMB16cjp9fN4zUAjN1DPA9ko6rAcYjYlX6WV+PiNvr1n8BcCVwftpY3qaH48KyOC6skWPCsjguuszdmXUoIr4vaTVwYv1oYGbauTQAkm4juRPzrgI+87OSdthmkl4AvA1YkrHIKSTtgF5LcunEusxxYVkcF9bIMWFZHBfdN5DZer+IpD87pQMk/eZ9nKSR+Dsj4vnAP5Nccjhf0iwl5jQGWTOShiTNqfvMben6ITlxGQc+CNwr6RjgEJLuS4iIXwLPiYiVU/umlofjwrI4LqyRY8KyOC66yzW+UzcbmK3kaSs/JjkLOqbW9iUiPifpSuA0kr73zidpNL5NUuOTUx6T9GjDuJkkwT+74TMB5kTErcCtSp7D/UngVpL2N6Sf/+upf0XrgOPCsjgurJFjwrI4LrrEN7cVSJLC/1Br4LiwLI4La+SYsCyOi2I58TUzMzOzSnAbXzMzMzOrBCe+ZmZmZlYJTnzNzMzMrBKc+JqZmZlZJTjxNTMzM7NK+P8BS4XvYuKKJR4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 5, figsize=(10, 4), sharex=True, sharey=True)\n",
    "fig.suptitle(\"样例1\", size=20)\n",
    "\n",
    "for i in range(2):\n",
    "    for j in range(5):\n",
    "        axs[i][j].scatter(np.random.randn(10), np.random.randn(10))\n",
    "        axs[i][j].set_title(\"%s行%s列\"%(i, j))\n",
    "        axs[i][j].set_xlim(-5, 5)\n",
    "        axs[i][j].set_ylim(-5, 5)\n",
    "        if i == 1 : axs[i][j].set_xlabel(\"横坐标\", fontsize=15)\n",
    "        if j == 0 : axs[i][j].set_ylabel(\"纵坐标\", fontsize=15)\n",
    "\n",
    "# 加入这个参数之后样例1和底下的文字就不会重叠了\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 使用 GridSpec 绘制非均匀子图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T02:10:32.427106Z",
     "start_time": "2020-12-19T02:10:31.597660Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,6))\n",
    "spec = fig.add_gridspec(2, 5, width_ratios=[1,2,3,4,5], height_ratios=[1,3])\n",
    "fig.suptitle(\"样例2\", fontsize=20)\n",
    "\n",
    "for i in range(2):\n",
    "    for j in range(5):\n",
    "        ax = fig.add_subplot(spec[i, j])\n",
    "        ax.scatter(np.random.randn(10), np.random.randn(10))\n",
    "        ax.set_title(\"%s行%s列\"%(i, j))\n",
    "        if i == 1 : ax.set_xlabel(\"横坐标\", fontsize=15)\n",
    "        if j == 0 : ax.set_ylabel(\"纵坐标\", fontsize=15)\n",
    "            \n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在上面的例子中出现了 spec[i, j] 的用法，事实上通过切片就可以实现子图的合并而达到跨图的共能"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T02:14:11.267119Z",
     "start_time": "2020-12-19T02:14:10.702497Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x16cd67d20a0>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 6))\n",
    "fig.suptitle(\"样例3\")\n",
    "spec = fig.add_gridspec(2, 5, width_ratios=[1,2,3,4,5], height_ratios=[1, 3])\n",
    "\n",
    "ax = fig.add_subplot(spec[0, 0:3])\n",
    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
    "\n",
    "ax = fig.add_subplot(spec[0, 3:4])\n",
    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
    "\n",
    "ax = fig.add_subplot(spec[1, 0:2])\n",
    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
    "\n",
    "ax = fig.add_subplot(spec[1, 2:4])\n",
    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
    "\n",
    "ax = fig.add_subplot(spec[0:2, 4:5])\n",
    "ax.scatter(np.random.randn(10), np.random.randn(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 子图上的方法"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在 ax 对象上定义了和 plt 类似的图形绘制函数，常用的有： plot, hist, scatter, bar, barh, pie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T02:20:03.547941Z",
     "start_time": "2020-12-19T02:20:03.414818Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x16cd66fb3a0>]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,3))\n",
    "\n",
    "ax.plot([1,2], [4,8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T02:20:23.990999Z",
     "start_time": "2020-12-19T02:20:23.837931Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  2.,  26.,  80., 154., 231., 261., 142.,  79.,  22.,   3.]),\n",
       " array([-3.13244926, -2.499888  , -1.86732674, -1.23476549, -0.60220423,\n",
       "         0.03035702,  0.66291828,  1.29547953,  1.92804079,  2.56060204,\n",
       "         3.1931633 ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,3))\n",
    "\n",
    "ax.hist(np.random.randn(1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T02:23:33.770361Z",
     "start_time": "2020-12-19T02:23:33.639145Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,3))\n",
    "\n",
    "# y=0, xmin=0, xmax=1\n",
    "ax.axhline(0.5, 0.2, 0.8)\n",
    "# x=0, ymin=0, ymax=1\n",
    "ax.axvline(0.5, 0.2, 0.8)\n",
    "# 从（0,0）到（1,1）\n",
    "ax.axline([0,0], [1,1])\n",
    "\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T03:57:20.705519Z",
     "start_time": "2020-12-19T03:57:20.550462Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.8, 0.2, '123123')"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.arrow(0, 0, 1, 2, width=0.02, head_length=0.05, facecolor='red', edgecolor='blue')\n",
    "ax.text(0.4, 1, s=\"123\", fontsize=16, rotation=90,rotation_mode='anchor', color='green')\n",
    "ax.annotate(\"123123\", xy=(0.6, 0.3), xytext=(0.8, 0.2), arrowprops=dict(facecolor='yellow', edgecolor='black'), fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-19T03:58:02.113527Z",
     "start_time": "2020-12-19T03:58:01.959290Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x16cd657efa0>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot([1,2],[2,1],label=\"line1\")\n",
    "ax.plot([1,1],[1,2],label=\"line1\")\n",
    "ax.legend(loc=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 作业"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 墨尔本1981年至1990年的每月温度情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-20T09:54:46.865780Z",
     "start_time": "2020-12-20T09:54:46.847828Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1981-01</td>\n",
       "      <td>17.712903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1981-02</td>\n",
       "      <td>17.678571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1981-03</td>\n",
       "      <td>13.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1981-04</td>\n",
       "      <td>12.356667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1981-05</td>\n",
       "      <td>9.490323</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Time  Temperature\n",
       "0  1981-01    17.712903\n",
       "1  1981-02    17.678571\n",
       "2  1981-03    13.500000\n",
       "3  1981-04    12.356667\n",
       "4  1981-05     9.490323"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ex1 = pd.read_csv('data/layout_ex1.csv')\n",
    "ex1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-20T10:23:48.134709Z",
     "start_time": "2020-12-20T10:23:47.279963Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,4))\n",
    "years = list(set([x.split(\"-\")[0] for x in ex1[\"Time\"]]))\n",
    "years.sort()\n",
    "fig.suptitle(\"墨尔本1981年至1990年月温度曲线\", fontsize=15)\n",
    "\n",
    "\n",
    "for n,year in enumerate(years):\n",
    "    n = n+1\n",
    "    data = ex1[ex1[\"Time\"].str.contains(year)]\n",
    "    ax = fig.add_subplot(2,5,n)\n",
    "    ax.plot(range(len(data[\"Time\"])), data[\"Temperature\"], marker=\"o\", markersize=3)\n",
    "    ax.set_ylim(0,20)\n",
    "    ax.set_yticks([5, 10, 15])\n",
    "    ax.set_xticks(range(len(data[\"Time\"])))\n",
    "    ax.set_title(\"%s年\"%year)\n",
    "    if n <=5:\n",
    "        ax.set_xticks([])\n",
    "    if n in [1, 6]:\n",
    "        ax.set_ylabel(\"气温\")\n",
    "\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-20T10:10:49.133153Z",
     "start_time": "2020-12-20T10:10:49.126172Z"
    }
   },
   "source": [
    "## 画出数据的散点图和边际分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-20T10:39:33.340164Z",
     "start_time": "2020-12-20T10:39:33.118424Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 75.6, -3.2633333333333336, 3.2633333333333336)"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.random.randn(2, 300)\n",
    "\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "spec = fig.add_gridspec(2, 2, width_ratios=[4,1], height_ratios=[1,4])\n",
    "\n",
    "# 直方图\n",
    "ax = fig.add_subplot(spec[0, 0])\n",
    "ax.hist(data[0], bins=np.linspace(-3,3,10), rwidth=0.9)\n",
    "ax.axis(\"off\")\n",
    "\n",
    "# 散点图\n",
    "ax = fig.add_subplot(spec[1, 0])\n",
    "ax.scatter(data[0], data[1])\n",
    "ax.set_xlim(-3,3)\n",
    "ax.set_ylim(-3,3)\n",
    "ax.grid(True)\n",
    "\n",
    "# 直方图\n",
    "ax = fig.add_subplot(spec[1, 1])\n",
    "ax.hist(data[1], bins=np.linspace(-3,3,10), rwidth=0.9, orientation=\"horizontal\")\n",
    "ax.axis(\"off\")"
   ]
  },
  {
   "cell_type": "code",
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